Response error and processing biases in confidence judgment

Previous studies showed that random error can explain overconfidence effects typically observed in the literature. One of these studies concluded that, after accounting for random error effects in the data, there is little support for cognitive‐processing biases in confidence elicitation. In this paper, we investigate more closely the random error explanation for overconfidence. We generated data from four models of confidence and then estimated the magnitude of random error in the data. Our results show that, in addition to the true magnitude of random error specified in the simulations, the error estimates are influenced by important cognitive‐processing biases in the confidence elicitation process. We found that random error in the response process can account for the degree of overconfidence found in calibration studies, even when that overconfidence is actually caused by other factors. Thus, the error models say little about whether cognitive biases are present in the confidence elicitation process. Copyright © 2008 John Wiley & Sons, Ltd.     

Sequential effects in dimensional contrast

Two experiments examined pigeons' response rates during short trials signaled by stimuli closely spaced along a wavelength continuum. In Experiment 1 separate halves of the continuum were correlated with different reinforcement schedules. In Experiment 2, the middle stimulus was accompanied by a lower probability of reinforcement than were the remaining wavelengths. Both procedures resulted in dimensional contrast “shoulders,” seen as relatively enhanced or depressed response rates in the presence of stimuli between the extreme of the continuum and the border separating the positive and negative stimuli. Sequential analyses addressed possible contributions of the following interactions: (a) local contrast, seen when rate during a given schedule depends on the schedule in the just-preceding trial; (b) modification of local contrast by the similarity of the signaling stimuli (P. Blough, 1983); and (c) schedule-independent rate contrast, seen when rate in a given trial depends on the rate controlled by the stimulus that accompanied the just-preceding trial (Malone & Rowe, 1981). Dimensional contrast functions were similar when isolated according to the schedule, to the similarity of the signaling stimulus, and to the response rate of the just-preceding trial. The interactions noted above do not appear to make important contributions to this effect.     

Millon Clinical Multiaxial Inventory (MCMI) computer-generated diagnoses: How do they compare to clinician judgment?

During the past several decades, computers have achieved increasing prominence in psychological assessment procedures. This is particularly true for computer-based test interpretation and diagnosis. This study reports on a study designed to compare the accuracy of computer-based diagnoses with clinician-generated diagnoses. The Millon Clinical Multiaxial Inventory (MCMI) was administered to 151 consecutively admitted inpatients at a large private psychiatric hospital. The computer-generated diagnoses were compared with those generated by admitting psychiatrists. The results indicated that the MCMI diagnostic impressions underestimated the severity of depressive disorders when compared with clinician diagnoses on Axis I. Specifically, clinicians diagnosed major depression much more frequently than did the MCMI. In addition, clinicians diagnosed anxiety disorders much less frequently than did the MCMI.     

An evaluation of the reliability of probability judgments across response modes and over time

Despite the importance of probability assessment methods in behavioral decision theory and decision analysis, little attention has been directed at evaluating their reliability and validity. In fact, no comprehensive study of reliability has been undertaken. Since reliability is a necessary condition for validity, this oversight is significant. The present study was motivated by that oversight. We investigated the reliability of probability measures derived from three response modes: numerical probabilities, pie diagrams, and odds. Unlike previous studies, the experiment was designed to distinguish systematic deviations in probability judgments, such as those due to experience or practice, from random deviations. It was found that subjects assessed probabilities reliably for all three assessment methods regardless of the reliability measures employed. However, a small but statistically significant decrease over time in the magnitudes of assessed probabilities was observed. This effect was linked to a decrease in subjects overconfidence during the course of the experiment.     

A Logic for Reasoning about Relative Similarity

A similarity relation is a reflexive and symmetric binary relation between objects. Similarity is relative: it depends on the set of properties of objects used in determining their similarity or dissimilarity. A multi-modal logical language for reasoning about relative similarities is presented. The modalities correspond semantically to the upper and lower approximations of a set of objects by similarity relations corresponding to all subsets of a given set of properties of objects. A complete deduction system for the language is presented.     

Upward versus Downward Anchoring in Frequency Judgments of Social Facts

Frequency estimation of social facts in two methods of judgment elicitation was investigated. In the “narrow-range” condition, subjects answered questions in the format: “Out of 100 incidents, how many belong to category X?” In the “wide-range” condition, the frequency for the same event was assessed with respect to “Out of 10,000”. Judged frequencies in the wide-range condition were divided by 100, and were compared with the corresponding judgments in the narrow-range condition. Such comparisons were made for low-frequency and high-frequency events. Previous research has shown that, for low-frequency events, judged frequencies are proportionally greater in the narrow-range than in the wide-range condition. These results reflect cognitive processes of implicit anchoring, whereby judged frequencies lie close to small numbers within the response ranges provided. I call this process “downward anchoring,” and predicted that this tendency would be replicated in the present study. Moreover, I predicted that assessments about high-frequency events would evoke similar cognitive processes operating in the opposite direction. By such “upward anchoring,” judged frequencies would lie close to relatively larger numbers within the given response ranges. Consequently, I predicted that judged frequencies for high-frequency events would be proportionally greater in the wide-range condition than in the narrow-range condition. These predictions were confirmed.     

Reflections on segregating and assessing areas of competence

Various complexities that arise in the application of legal and/or clinical criteria to the actual assessment of competence/capacity are discussed, and a particular way of understanding the nature of such criteria is recommended.     

Calibration of sensory and cognitive judgments: A single model for both

In a recent issue of this journal, Winman and Juslin (34 , 135–148, 1993) present a model of the calibration of subjective probability judgments for sensory discrimination tasks. They claim that the model predicts a pervasive underconfidence bias observed in such tasks, and present evidence from a training experiment that they interpret as supporting the notion that different models are needed to describe judgment of confidence in sensory and in cognitive tasks. The model is actually part of the more comprehensive decision variable partition model of subjective probability calibration that was originally proposed in Ferrell and McGoey (Organizational Behavior and Human Performance, 26 , 32–53, 1980). The characteristics of the model are described and it is demonstrated that the model does not predict underconfidence, that it is fully compatible with the overconfidence frequently found in calibration studies with cognitive tasks, and that it well represents experimental results from such studies. It is concluded that only a single model is needed for both types of task.     

Similarities derived from 3-d nonlinear psychophysics: Variance distributions

Many-one mappings between stimulus properties and pairwise generated similarities are intrinsic to definitions of similarity. This of itself is not sufficient as a basis for predicting the variance associated with any single similarity judgment. An extension to cover this has to be made either by making ancillary assumptions about noise, or by using nonlinear models. The derivation of the variance of similarity judgments is made from the 3 process in nonlinear psychophysics. The idea of separability of dimensions in metric space theories of similarity is replaced by one parameter which represents the degree of a form of interdimensional crosscoupling